We are building Sclera, an extensible SQL engine that enables you to push your analytics operations into a SQL query. The idea is to tame the code complexity through a declarative interface to analytics libraries. You can add your own libraries using the Sclera Extensions SDK. http://www.scleradb.com/doc/sdk/sdkintro
From the FAQ: http://www.scleradb.com/doc/info/faq#i-am-an-analytics-consu...
why-do-i-need-sclera
> Specifically, Sclera separates the analytics logic from the processing and data access. The analytics logic is specified declaratively as SQL queries with Sclera’s analytics extensions. This is just a few lines of code, which can be changed easily. The analytics libraries, database systems and external data sources form their own modules and are separated from the analytics logic. The analytics queries are compiled by Sclera into optimized workflows that dynamically tie everything together.
Done that -- the best career decision I ever made. Left for a startup after several years in a corporate research lab.
Think of this transition as going back to school (because that is exactly what it is!). If anything, this will increase your employability, so your job-insecurity issues are unfounded.
OP talks about performance optimization, not about "infrastructure work" in general.
The issue with performance optimization is that fast enough systems are ok -- nobody needs the fastest system possible. So its not much of an optimization, really.
If you are spending time scaling stuff that is fast enough, you are not spending your resources well. Naturally, you will not be appreciated. On the other hand, if you resolve a critical scalability issue, you will certainly be recognized as a hero.
From the FAQ: http://www.scleradb.com/doc/info/faq#i-am-an-analytics-consu... why-do-i-need-sclera > Specifically, Sclera separates the analytics logic from the processing and data access. The analytics logic is specified declaratively as SQL queries with Sclera’s analytics extensions. This is just a few lines of code, which can be changed easily. The analytics libraries, database systems and external data sources form their own modules and are separated from the analytics logic. The analytics queries are compiled by Sclera into optimized workflows that dynamically tie everything together.